说明：  　　本文主要介绍怎样使用opencv来对图片进行傅里叶变换，其核心函数是opencv自带的dft()。DFT这个技术手段是将空间域映射到频率域中去，在图像处理有着举足轻重的地位。这里我们只是得到其变换的结果并看看贫域图有什么特点。 　　实验功能： 单击Open Image按钮，手动选择打开一副图片，不管其是否是彩色图片，这里统一将其转换成灰度图像显示，因为需要加快DFT运算速度。 将鼠标移动到图片显示区域，单击图片，这时会显示DFT中间结果图，也就是没有将低频域的点移动到图片的中心而已。显示的图片有文字提示。 继续单击图片，会显示最后重新布局后的DFT结果图，当然也有相应的文字提示。 继续单击图片时，则原图，dft未调整图，dft调整图这3幅图片会进行轮流切换显示。
(This article describes how to use opencv to the Fourier transform of the picture, its core functions is the the opencv comes with the dft (). DFT techniques is mapping the spatial domain to the frequency domain has a pivotal position in the image processing. Here we just get the transformation of the results and see what are the characteristics of poor domain map. Experimental feature: Click on the Open Image button to manually choose to open a picture, regardless of whether it is a color picture here unified convert to grayscale images, because of the need to accelerate the speed of the DFT operation. Move the mouse to the image display area, click the picture, then displays the DFT intermediate results diagram, that is, no low-frequency domain to point to move to the center of the picture. Shown in the picture text prompts. Click the picture, will show that the DFT results after the last re-layout diagram, of course, there is a corresponding text prompts. Continue to click the pictur)